This update from the π-HuB Secretariat brings you a landmark longitudinal proteomics advance led by Professor Jing Liu, Professor Ruiping Xiao and Professor Jinzhou Wang, published in Nature Health with the title Temporal dynamics of the human blood proteome in ageing and disease. Addressing a critical gap in precision ageing and medical proteomics, this 20-year population-based cohort study establishes the first systematic atlas of human blood proteome long-term stability, providing a novel methodological framework for reliable biomarker screening and individualized health monitoring.

Current blood proteome research for ageing and disease prediction heavily relies on single-time-point sampling strategies. However, acute physiological fluctuations, environmental interference, and technical variability often compromise the representativeness of one-off measurements for individual long-term health status. To resolve this bottleneck, the research team leveraged the Chinese Multi-provincial Cohort Study (CMCS) with repeated blood sampling across two decades, systematically quantified the temporal stability of over 10,000 circulating proteins, and proposed the innovative Protein Homeostatic Index (PHI) to standardize the evaluation of long-term proteomic stability.

Research Strategy

The study adopted a rigorous long-term longitudinal cohort design combined with multi-platform external validation, forming a complete research system from atlas construction to clinical translational verification:

1. Twenty-year longitudinal cohort setup: A total of 2,621 participants from the CMCS cohort were enrolled, with 5,458 proteomic measurements collected across four key time points (2002, 2007, 2012, 2022). Among them, 1,298 individuals with at least two valid proteomic datasets were included for core PHI analysis.

2. High-throughput proteomic profiling: All samples were quantified via the SomaScan 11K platform, covering 10,776 protein biomarkers to achieve full-proteome stability profiling.

3. Standardized PHI quantification: After age and gender correction, intra-individual Pearson correlation coefficients across different follow-up intervals were used to calculate PHI, accurately reflecting the temporal consistency of individual protein relative levels.

4. Cross-cohort and cross-platform validation: The UK Biobank longitudinal Olink dataset was applied to verify the repeatability of PHI and evaluate its cross-platform transferability for robust result confirmation.

Core Research Results

1. Intrinsic heterogeneous proteome stability. The 10,776 profiled proteins showed distinct long-term stability heterogeneity. Protein PHI values were highly consistent across 5-year and 20-year intervals, confirming temporal stability is an intrinsic molecular trait rather than a time-dependent artifact. Stability rankings were largely consistent across sexes and age groups, with slightly higher PHI observed in females and the elderly population, reflecting life-stage-specific homeostatic regulation differences.

2. Genetic and environmental regulators of stability. High-PHI proteins were strongly governed by genetic factors with elevated pQTL effects, while long-term environmental and lifestyle exposures also sustained stable proteomic signatures. Notably, proteins encoded by the same gene exhibited moderate PHI correlation, indicating isoform variation and post-translational modifications shape individual temporal stability features.

3. Functional characteristics of stable proteins. High-stability circulating proteins were enriched in secreted and immune membrane proteins responsible for systemic signal regulation and immune homeostasis. By contrast, low-stability intracellular proteins in peripheral blood mainly reflect transient tissue injury and cell turnover, explaining their poor temporal consistency.

4. Platform-dependent PHI transferability. Validated in the UK Biobank Olink cohort, PHI exhibited robust intra-platform repeatability. However, cross-platform generalization was limited to proteins with high measurement consistency between SomaScan and Olink, reminding the field to avoid simplistic cross-platform molecular equivalence assumption based merely on gene annotation.

5. Improved clinical biomarker panels. Incorporating PHI into biomarker optimization improved the performance of ageing clock models. Replacing unstable proteins in the classic ProtAge20 panel with high-PHI age-related proteins enhanced prediction for mortality and age-related diseases in a large-scale cohort of 45,441 participants. Stable markers including LPA and GDF15 serve as reliable lifelong risk biomarkers, and 21 high-PHI proteins can indicate individualized homeostatic deviation, which independently predicts all-cause mortality beyond conventional population-based metrics.

Study Summary

Different from conventional studies that merely screen disease-associated proteins, this research innovatively introduces temporal stability as a core evaluation criterion for proteomic biomarkers. It establishes a quantitative PHI framework to distinguish stable individual-specific molecular fingerprints from transient fluctuating signals. Most importantly, it upgrades the precision medicine paradigm from population-based threshold judgment to individualized baseline comparison, laying a solid methodological foundation for longitudinal health monitoring and accurate ageing risk stratification.

Relevance for the Scientific Mission of π-HuB

This study aligns closely with π-HuB’s core mission of advancing human proteome research for precision health and translational medicine. It provides a standardized stability evaluation system for biomarker development, addressing the key technical challenge of sampling time bias in omics research. The cross-cohort, cross-platform validation paradigm sets a high-standard reference for global longitudinal proteome studies. Moreover, the individualized homeostatic monitoring framework offers a novel implementation path for π-HuB’s population-based precision health research, facilitating unified technical specifications for reliable clinical proteomic translation.

We warmly congratulate Professor Jing Liu, Professor Ruiping Xiao, Professor Jinzhou Wang and all collaborators on this pivotal achievement. The π-HuB Secretariat will continue to track cutting-edge global proteomic advances, strengthen academic exchange and partnership linkage within the community, and support collaborative research on standardized biomarker development and precision health applications.

Reference

Wu, W., Yang, Z., Cheng, L. et al. Temporal dynamics of the human blood proteome in ageing and disease. Nat. Health (2026). https://doi.org/10.1038/s44360-026-00183-1